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Foundational Python for Data Science Kennedy Behrman

Foundational Python for Data Science By Kennedy Behrman

Foundational Python for Data Science by Kennedy Behrman


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Foundational Python for Data Science Summary

Foundational Python for Data Science by Kennedy Behrman

Data science and machine learning - two of the world's hottest fields - are attracting talent from a wide variety of technical, business, and liberal arts disciplines. Python, the world's #1 programming language, is also the most popular language for data science and machine learning. This is the first guide specifically designed to help millions of people with widely diverse backgrounds learn Python so they can use it for data science and machine learning. Leading data science instructor and practitioner Kennedy Behrman first walks through the process of learning to code for the first time with Python and Jupyter notebook, then introduces key libraries every Python data science programmer needs to master. Once you've learned these foundations, Behrman introduces intermediate and applied Python techniques for real-world problem-solving. Throughout, Foundational Python for Data Science presents hands-on exercises, learning assessments, case studies, and more - all created with Colab (Jupyter compatible) notebooks, so you can execute all coding examples interactively without installing or configuring any software.

About Kennedy Behrman

Kennedy Behrman is a veteran software and data engineer. He first used Python writing asset management systems in the Visual Effects industry. He then moved into the startup world, using Python at startups using machine learning to characterize videos and predict the social media power of athletes.

Table of Contents

I. Learning Python in a Notebook Environment 1. Python Past and Future 2. Introduction to Colab 3. Fundamentals of Python 4. Sequences 5. Other Python Data Structures 6. Data Conversion Recipes 7. Execution Control 8. Functions in Python II. Data Science Libraries 9. What is numpy? 10. Learn sklearn 11. Learn pandas 12. Learn TensorFlow & Keras 13. Use seaborn for 2D Plots 14. Use Plotly for Interactive Plots 15. Specialized Visualization Libraries 16. Learn Natural Language Processing Libraries III. Fundamentals of Math & Statistics for Data Science 17. Math Python Standard Library 18. Scipy for Statistics & Probability 19. Statistics Python Standard Library IV. Visualization 20. Interactive Data Visualization 21. Publishing Data Visualizations V. Fundamentals of Machine Learning for Data Science 22. Learn the Basics of Machine Learning 23. Unsupervised Machine Learning 24. Understand the Fundamentals of Unsupervised Learning 25. Supervised Machine Learning 26. EDA (Exploratory Data Analysis) VI. Intermediate Python 27. Working on a Python Project in an Editor 28. Functional Programming 29. Lazy Evaluation/Generators 30. Object-Oriented Programming 31. Sorting 32. Pattern Matching 33. I/O VII. Applied Topics in Data 34. Deep Learning Keras PyTorch 35. Big Data Spark 36. Open Source AutoML Ludwig H2O Auto-Keras 37. Building a Portfolio Appendices Appendix A: Answers to Selected Exercises Appendix B: Instructor Manual

Additional information

NGR9780136624356
9780136624356
0136624359
Foundational Python for Data Science by Kennedy Behrman
New
Paperback
Pearson Education (US)
2022-01-06
256
N/A
Book picture is for illustrative purposes only, actual binding, cover or edition may vary.
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